sids blog

When I decided to go deep into AI, I started by reading science fiction stories about AI and broad general books on the subject. My primary goal was to develop genuine curiosity, so that studying AI wouldn’t feel like work but more like play. Once I became deeply curious, I wanted to understand its history—what happened in the past and how we arrived at the present. The logical next step was to pick up an AI textbook and truly grasp the fundamentals: how it works, why it works, what needs to be done right, and what the first principles are.

Whenever people ask me about my progress, they always have one piece of advice: “What are you doing? You should focus on learning ML and start doing projects—code!”

But if I skip the fundamentals and jump straight into building ML/DL models:

• I will build AI but won’t understand why it works.
• I won’t be able to adapt when AI evolves beyond current models.
• I will get stuck competing in an already saturated field.

What I really need to focus on is:

• Understanding the limitations of current AI and identifying what’s missing.
• Thinking beyond the hype cycle and seeing where AI is truly headed.

This is the problem with people who don’t grasp the fundamentals. Current AI is model-based, reflexive AI—that ship has already sailed. I’m already late to that party. If I focus on what’s trending now instead of deeply understanding the foundations, I’ll miss the next AI revolution. The future lies in developing goal-based AI systems, utility-based AI systems, and eventually AGI. I need to position myself strategically to exploit these upcoming opportunities instead of chasing whatever is popular today.

I want to be in the same position as Bill Gates when he realized software was the future while everyone else was focusing and competing in hardware. By understanding AI at its core, I can anticipate the next transformation rather than just following the current trends.